Staff Research Engineer, Embodied Intelligence & Robotics at Samsung Research America
Mountain View, CA 94043, USA -
Full Time


Start Date

Immediate

Expiry Date

30 Nov, 25

Salary

246150.0

Posted On

31 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Kinematics, Object Detection, Cuda, Ros, Image Processing, 3D Mapping, Writing, Dynamics, C++, Segmentation, Model Predictive Control, Data Quality, Training, Slam

Industry

Information Technology/IT

Description

Lab Summary: The Robot Intelligence Lab at Samsung Research America is a new facility dedicated to advancing the field of robotics through cutting-edge research and development. The lab’s mission is to develop advanced technologies to power intelligent robotic systems capable of manipulation, navigation, and complex reasoning for a variety of high-impact application areas. To achieve this mission, the lab collaborates closely with external entities such as universities, startups, and government labs, as well as with several Samsung Product and Advanced Research labs.
Position Summary: Samsung Research America is looking for an engineer who has solid technical skills and rich academic and/or industry experience in areas of robotics and embodied intelligence. Our ideal candidate explores novel AI technologies towards generalizing robots to perform tasks in the real world. Samsung’s unique advantage in the consumer electronics market and growing focus on AI and robotics will provide you with exciting technical challenges and a rewarding career experience. By leveraging Samsung’s vast product ecosystem to deliver novel user experiences, your work will define Samsung’s future in robotics and significantly impact real-world users.

REQUIRED SKILLS:

  • PhD or Master’s degree in EECS/Robotics or equivalent combination of education, training, and experience
  • 3+ years’ industry experience in state-of-the-art robotics R&D, such as foundation models, vision-language-action (VLA) models, open-world 3D perception, trajectory prediction, model predictive control, and multimodal (visual, tactile, audio, semantic) information fusion
  • Demonstrated experience in sensing, kinematics, dynamics, and control systems integrated on real robotic systems
  • Solid understanding of computer vision techniques (e.g., object detection, segmentation, tracking) and multi-view image processing
  • Knowledgeable of tools and processes to monitor ML model performance and data quality, including model tuning experience
  • Familiarity with PyTorch, TensorFlow, C++, ROS, and CUDA
  • Demonstrated experience in software engineering best practices to track, communicate, and document project progress
  • Strong understanding of robotics fundamentals, including locomotion, manipulation, sensor inputs, pose tracking, 3D mapping, SLAM, ROS, and policy architectures particularly for semi-structured and unstructured environments
  • Excellent problem-solving skills and the ability to work independently and as part of a team
  • Excellent verbal communication and writing skills to effectively represent the derived results and technical concepts developed in the course of the work
    Candidates with additional experience are encouraged to apply in and will be considered for other opportunities.
Responsibilities
  • Design and evaluate the suitability of robotic hardware, sensors, and software for applications in semi-structured and unstructured environments targeting high impact business areas
  • Integrate sensors, actuators and other component into proof-of-concept/prototype robotic systems and analyze and optimize robotic system performance and accuracy
  • Design, develop, integrate and test algorithms for robot perception, control, learning, navigation, and manipulation
  • Develop and deploy data collection and model management mechanisms for in-the wild data aggregation
  • Work within cross-functional, cross-divisional teams and assist in the design, analysis and performance evaluation from concept to completion
  • Document and present results evaluating algorithms and models on targeted compute platforms
  • Conduct pilot studies and formal experiments to benchmark performance against state-of-the-art approaches using clear and well-reasoned metrics
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